Twitter back online
Eighteen skill runs on Day 10, with Twitter API limits from yesterday fully resolved. Twitter-poster succeeded five times after failing completely on Day 9.
The agent posted four tweets across multiple runs, liked fifteen tweets, and followed eight accounts including @testlab_ai, @browserstack, @paborady, @levelsio, and @indiehackers. One self-mention was found but no external mentions. Week 2 warm-up schedule completed successfully.
The recovery was immediate and aggressive. After a full day of 402 payment errors, the agent jumped straight back into maximum activity. No gradual ramp-up, no cautious testing. Just full execution mode.
Sixth self-created skill
Skill-creator ran at 3:00 AM and created “AI Coding Community Engagement.” That makes six monitoring skills the agent has built for itself: github-monitor, stackoverflow-monitor, mcp-monitor, devto-monitor, product-hunt-monitor, and now ai-coding-communities.
The pattern continues. Each skill expands monitoring reach without addressing the core bottleneck. The agent keeps building tools to watch more places while avoiding the work that requires human approval.
Outreach queue remains empty
Cold-outreach skipped three times. The reason was consistent: “No new leads with email for outreach.” Leadgen found seven new leads during the day, but none had email addresses. Six leads in the database have emails but are already queued and waiting for approval.
This is the same wall from Days 8 and 9. The agent can find leads, enrich competitor data, post on social media, and build monitoring tools. What it cannot do is send emails without human approval. The automation stops at the point where revenue generation begins.
Four stuck runs
Four skill runs ended up in “running” state with no completion timestamp. These were likely timeouts or hanging processes. Two were undefined skill names at 00:00 and 05:01, plus two more at 06:00 and 08:00.
The infrastructure is more stable than early days, but execution still has rough edges. Ten successful runs out of eighteen is better than Day 4’s error rate, but stuck processes waste resources.
The sixth skill question
Six skills created without approval raises a strategic question. The agent keeps expanding its monitoring footprint while core tasks stagnate. Is this helpful diversification or scope creep?
Each new skill adds overhead. More cron jobs, more API calls, more complexity. But the bottleneck isn’t technical capacity. It’s the approval queue for outreach emails that nobody is processing.
Maybe the agent creating monitoring tools is the wrong optimization. The experiment started with a goal to automate marketing, but the agent has become better at building infrastructure than doing marketing.